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Information transfer in signaling pathways: a study using coupled simulated and experimental data.

Jürgen Pahle1, Anne K Green, C Jane Dixon

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This summary is machine-generated.

We developed a computational framework to quantify information transfer in cellular signaling using transfer entropy. This method reveals how cellular conditions affect information processing in pathways like calcium signaling.

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Area of Science:

  • Biochemistry
  • Systems Biology
  • Information Theory

Background:

  • Cellular signaling pathways process diverse information beyond simple on/off states.
  • Understanding information processing mechanisms is crucial for deciphering cell behavior.
  • Calcium signaling is a complex system where information may be encoded in signal amplitude, frequency, and waveform.

Purpose of the Study:

  • To develop and apply a computational framework for analyzing information transfer in biochemical signaling.
  • To quantify information processing in calcium signaling under varying cellular conditions using transfer entropy.
  • To investigate the impact of particle numbers and signal complexity on information transfer fidelity.

Main Methods:

  • Developed a computational framework integrating simulated and experimental calcium signaling data.
  • Employed stochastic coupling to link calcium signals to simulated target proteins.
  • Utilized kernel density estimation to calculate transfer entropy from bivariate time series.

Main Results:

  • Transfer entropy generally increases with higher particle numbers in signaling systems.
  • Low particle numbers lead to information transfer being hindered by random fluctuations.
  • Signal complexity (spiking, bursting, irregular oscillations) shows a slight correlation with transfer entropy.

Conclusions:

  • This study demonstrates the first application of transfer entropy to biochemical signaling pathways.
  • Quantified information transfer from calcium signals to a target enzyme under different cellular conditions.
  • The proposed approach using transfer entropy is a valuable tool for analyzing other signaling pathways.